Widespread adoption of wireless communication standards has led to a proliferation of networks. Notable examples include systems based on the IEEE 802.11 protocols. With this growth, there has been a concurrent increase in the functionality provided by such networks. A particularly desirable feature is the ability to make positioning determinations for nodes within the network by analyzing the transmissions between the nodes. The benefits associated with such a capability are numerous.
One important application relates to the tracking of assets or people. By providing an entity with a transceiver in communication with the wireless network, its position can be determined rapidly. With regard to assets, knowledge of current position facilitates utilization of the asset, streamlines logistics and helps prevent loss. With regard to persons, management and oversight can be significantly improved.
Another application currently receiving considerable attention is Location-Based Services (LBS). With the availability of position information for mobile clients, the user of such a device can receive information specifically tailored to the user's current location. As will be appreciated, the benefits associated with this feature extend to multiple situations, including recreation, commercial and work environments.
In view of the desirability of providing network nodes having position determination capabilities, a number of strategies have been employed to perform the necessary determinations. Many of the location techniques used in wireless networks are based on electromagnetic analyses of the characteristics of communications between nodes of the network. For example, received signal strength indication (RSSI), time-of-arrival (TOA), time-difference-of-arrival (TDOA) and round trip time (RTT) can all be used to make estimations of the distance between participating nodes. With sufficient numbers of distance estimations between a node with unknown position and nodes having known position, range-based location determinations such as trilateration are possible. Alternatively, angle-of arrival (AOA) can also be used with suitable triangulation algorithms to make position determinations, but such techniques typically require use of an antenna array to obtain the necessary signal angle information.
To obtain the benefits of making position determinations for network nodes in a wireless network, a number of challenges must be met. In one important aspect, the distance estimations used for range-based solutions require are subject to uncertainties resulting from many of the same noise and interference issues that effect wireless communication in general. For example, multipath distortion affecting the wireless channel may lead to distance estimates that do not correspond to the straight line path between the nodes. As will be appreciated, multipath propagation errors are typically exacerbated in indoor environments due to the many reflecting surfaces.
Accordingly, position determination in a wireless network environment requires robust strategies for managing noise and interference so that useful estimations can be made. Conventional methods for dealing with noise and interference include the use of data fitting algorithms such as a least squares-based analysis. Under these approaches, position determinations can often be improved by mitigating noise using filtering techniques including the use of Kalman filters and the like. In general, these methods provide relatively good position determinations when ample, high quality measurements are available.
The above noted conventional approaches are less successful, however, when only more sporadic measurements are available. In many practical situations, then, there may be an insufficient number of range measurements to obtain reliable position determinations. Further, relative motion between the network nodes also significantly undermines the ability of conventional techniques to provide sufficiently accurate position determinations. In addition to the noise imparted by motion, movement of one or more nodes may also render older measurements unusable.
As a result, it would be desirable to provide position determination for wireless networks even when relatively few measurements are available. Moreover, it would be desirable to provide such position determination using measurements taken at different times, even when relative motion between nodes may occur. Yet further, it would be desirable to provide such position determination so that the quality of the determination may be easily assessed. It would also be desirable to reduce the filtering necessary to obtain position determinations. This invention accomplishes these and other goals.